Industrial robot multi-task operation cooperative control method and system

Abstract

The invention relates to the technical field of robot control, and provides an industrial robot multi-task operation cooperative control method and system, and the method comprises the steps: obtaining the theoretical position information of each of a plurality of industrial robots on a production line after the current moment; the theoretical position information is position information of the geometric center of the industrial robot; for each industrial robot, determining a redundant safety space of the industrial robot according to the theoretical position information of the industrial robot; the industrial robot is located in the redundant safety space in the operation process; and in response to task instruction information for the target industrial robot in the plurality of industrial robots, determining task control information of the target industrial robot according to the task instruction information and the redundant safety space of each industrial robot in the plurality of industrial robots. Through the scheme, the multi-task operation cooperative control efficiency of the industrial robot can be improved.

Description

Technical Field

[0001] This application relates to the field of robot control technology, and in particular to a method and system for multi-task collaborative control of industrial robots. Background Technology

[0002] On modern intelligent manufacturing production lines, multiple industrial robots collaborate to complete complex tasks such as welding, handling, and assembly to ensure smooth and efficient production processes. However, in practical applications, the actual operating time of a single industrial robot can fluctuate unpredictably due to physical environmental factors. These fluctuations accumulate and cause a time discrepancy between the actual state of the industrial robot and the process model preset by the central system.

[0003] For example, on an automated automotive chassis production line, multiple industrial robots collaborate to complete the assembly process. The central control system generates detailed motion command sequences and conflict-free motion paths for each robot based on a pre-set process flow model. However, when welding robot D is performing its task, the actual welding time is not constant. Factors such as electrode consumption, minor oil or oxide layers on the workpiece surface, and voltage fluctuations can all extend the welding time at a single point. These minor delays accumulate during continuous operation, causing robot D to complete its task slower than planned. The central control system plans the entire production cycle based on idealized welding times. When robot D's actual operation is delayed, subsequent robots, such as robot E, will be idle and waiting because robot D has not yet left the production line, disrupting the entire production line's cycle and reducing efficiency.

[0004] In a context where slight deviations have already occurred in the production cycle, when the production line needs to perform global replanning based on changing circumstances in response to high-priority temporary tasks, the central control system generates new motion commands and paths for the industrial robots based on its internally lagging state model. For example, when the system instructs industrial robot A to grasp a special type of suspension bracket and plans for it to quickly pass through the edge of industrial robot D's work area, the system model indicates that industrial robot D should have already completed welding and returned to a safe position. However, in reality, due to the accumulated delays, industrial robot D is still performing the finishing work on the last weld point, with its welding torch and robotic arm still within the work area. This asynchrony causes industrial robot A's robotic arm to collide with industrial robot D's welding torch when executing new commands, resulting in equipment damage and production interruption. Summary of the Invention

[0005] This application provides a method and system for collaborative control of multi-task operation of industrial robots, aiming to solve the technical problems in modern intelligent manufacturing production lines where industrial robots are out of sync with the preset process model due to fluctuations in actual operation time, which leads to disruption of production rhythm, reduced efficiency, and even collisions between industrial robots due to information asynchrony when responding to temporary task replanning, causing equipment damage and production interruption.

[0006] To achieve the above objectives, this application adopts the following technical solution: Firstly, a method for collaborative control of multi-task operation of industrial robots is provided, comprising: acquiring the theoretical position information of each of the multiple industrial robots on the production line after the current moment; the theoretical position information being the position information of the geometric center of the industrial robot; determining the redundant safety space of each industrial robot based on its theoretical position information; the industrial robot being located within the redundant safety space during operation; and, in response to the task instruction information of the target industrial robot among the multiple industrial robots, determining the task control information of the target industrial robot based on the task instruction information and the redundant safety space of each of the multiple industrial robots.

[0007] Furthermore, the redundant safety space of the industrial robot is determined based on its theoretical position information, including: acquiring the historical theoretical position information and historical actual position information of the industrial robot at each historical moment in multiple historical moments; determining the spatial redundancy distance of the industrial robot based on the historical theoretical position information and historical actual position information at each historical moment in multiple historical moments; and determining the redundant safety space of the industrial robot based on the spatial redundancy distance and the theoretical position information of the industrial robot.

[0008] Based on this, the spatial redundancy distance of the industrial robot is determined according to the historical theoretical position information and historical actual position information of each historical moment in multiple historical moments. This includes: determining the root mean square error between the historical theoretical position information and the historical actual position information based on the historical theoretical position information and historical actual position information of each historical moment in multiple historical moments; obtaining the safety factor of the industrial robot; and using the product of the root mean square error and the safety factor of the industrial robot as the spatial redundancy distance of the industrial robot.

[0009] Furthermore, obtaining the safety factor of the industrial robot includes: obtaining the safety requirement index of the production line and a first correspondence; the first correspondence includes a one-to-one correspondence between multiple safety requirement index ranges and multiple first safety factors; taking the first safety factor corresponding to the safety requirement index range in which the production line's safety requirement index falls in the first correspondence as the production line safety factor; obtaining the running time of the industrial robot after its last maintenance and a second correspondence; the second correspondence includes a one-to-one correspondence between multiple running time ranges and multiple second safety factors; taking the second safety factor corresponding to the running time range in which the industrial robot's running time after its last maintenance falls in the second correspondence as the running time safety factor; and taking the weighted sum of the production line safety factor and the running time safety factor as the industrial robot's safety factor.

[0010] In some preferred embodiments, the position information of the industrial robot includes the theoretical position information of the industrial robot at each time after the current time. The redundant safety space of the industrial robot is determined based on the spatial redundancy distance and the theoretical position information, including: acquiring the outline of the industrial robot; for each time after the current time, using the theoretical position information of the industrial robot as the geometric center of the initial redundant safety space, and using the spatial redundancy distance corresponding to each time as the distance from the boundary of the initial redundant safety space to the corresponding position of the outline of the industrial robot, thus obtaining the initial redundant safety space of the industrial robot; the outline of the initial redundant safety space of the industrial robot is similar to the outline of the industrial robot; acquiring the planned operating speed of the industrial robot at each time after the current time; for each time after the current time, adjusting the initial redundant safety space of the industrial robot according to the planned operating speed of the industrial robot at each time, thus obtaining the redundant safety space of the industrial robot.

[0011] More specifically, the initial redundant safety space of the industrial robot is adjusted according to the planned operating speed of the industrial robot at each moment to obtain the redundant safety space of the industrial robot. This includes: obtaining a third correspondence for each moment after the current moment; the third correspondence includes a one-to-one correspondence between multiple operating speed ranges and multiple stretching coefficients; taking the stretching coefficient corresponding to the operating speed range of the planned operating speed of the industrial robot at each moment in the third correspondence as the target stretching coefficient for each moment; stretching the initial redundant safety space of the industrial robot along the direction of movement of the industrial robot according to the target stretching coefficient for each moment to obtain the redundant safety space of the industrial robot.

[0012] As a technological improvement, in response to the task instruction information of the target industrial robot from multiple industrial robots, the task control information of the target industrial robot is determined based on the task instruction information and the redundant safety space of each industrial robot. This includes: in response to the task instruction information of the target industrial robot from multiple industrial robots, determining the initial task control information of the target industrial robot based on the task instruction information; the initial task control information includes the initial position information and initial running speed of the target industrial robot at each moment when performing the task; inputting the position information of the target industrial robot at each moment when performing the task and the redundant safety space of each industrial robot into a preset geometric collision detection model to obtain the minimum distance between the target industrial robot and the redundant safety space of each industrial robot at each moment when performing the task; taking the moment when the corresponding minimum distance is less than 0 as the target moment; adjusting the initial task control information of the target industrial robot according to the minimum distance corresponding to the target moment, and obtaining and executing the adjusted task control information.

[0013] To improve the solution, the initial task control information of the target industrial robot is adjusted based on the minimum distance corresponding to the target industrial robot at the target time, and the adjusted task control information is obtained and executed. This includes: determining whether the absolute value of the minimum distance corresponding to the target time is less than a first distance threshold; when the absolute value of the minimum distance corresponding to the target time is less than the first distance threshold, the initial position information of the target industrial robot at the target time is translated along the target direction by the absolute value of the minimum distance, and the adjusted task control information is obtained and executed; the target direction is the direction in which the pre-collision industrial robot points to the target robot, and the pre-collision industrial robot is the industrial robot whose minimum distance between the redundant safety space and the target industrial robot at the target time is less than or equal to 0.

[0014] As a further improvement, when the absolute value of the minimum distance corresponding to the target time is greater than or equal to the first distance threshold, the initial task control information of the target industrial robot is adjusted to obtain and execute the adjusted task control information, including: reducing the planned running speed of the pre-collision industrial robot within a preset time period before the target time by a preset speed step; reducing the running speed of the target industrial robot within a preset time period before the target time by a preset speed step to obtain the initially adjusted task control information.

[0015] Secondly, this application also discloses a multi-task collaborative control system for industrial robots, comprising: an acquisition device and a processing device; the acquisition device is used to acquire the theoretical position information of each of the multiple industrial robots on the production line after the current moment; the theoretical position information is the position information of the geometric center of the industrial robot; the processing device is used to determine the redundant safety space of each industrial robot based on the theoretical position information of the industrial robot; the industrial robot is located within the redundant safety space during operation; the processing device is used to respond to the task instruction information of the target industrial robot among the multiple industrial robots, and determine the task control information of the target industrial robot based on the task instruction information and the redundant safety space of each of the multiple industrial robots. Beneficial effects

[0016] This application discloses a multi-task collaborative control method for industrial robots. By acquiring the theoretical position information of each industrial robot on the production line after the current moment, and determining the redundant safety space of each robot based on this theoretical position information, the method ensures that the industrial robot remains within its redundant safety space during operation. When the system responds to task command information for the target industrial robot, this method comprehensively considers the task command information and the redundant safety spaces of all industrial robots to determine the task control information for the target industrial robot.

[0017] This method effectively solves the problem in existing technologies where fluctuations in the actual operation time of individual industrial robots lead to asynchrony with the preset process model of the central system. On traditional production lines, even small operational delays accumulate, causing deviations between the actual state of the industrial robot and the system model, disrupting the production cycle and even triggering collisions between industrial robots during emergency replanning. This application introduces the concept of a "redundant safety space" and dynamically determines this space based on the theoretical position information of the industrial robots, enabling the system to monitor the safety boundaries of each industrial robot in real time. When planning tasks for a target industrial robot, the system no longer relies solely on an idealized preset model but incorporates the actual safety space information of all industrial robots, thereby generating safer and more reliable task control information.

[0018] Accordingly, this application can effectively avoid the collision risk caused by information asynchrony between industrial robots. For example, in an automated production line for automotive chassis, when industrial robot A needs to quickly pass through the working area of ​​industrial robot D, even if industrial robot D is still within the working area due to accumulated delays, this method can still plan a conflict-free path for industrial robot A using its redundant safety space information, thereby avoiding equipment damage and production interruptions. In this way, this application significantly improves the coordination and safety of multi-task operations, ensuring the smooth operation and efficient production of the production line. Attached Figure Description

[0019] Figure 1 A flowchart illustrating a multi-task collaborative control method for industrial robots provided in this application; Figure 2 A flowchart illustrating another industrial robot multi-task collaborative control method provided in this application; Figure 3 This application provides a schematic diagram of the architecture of a multi-task collaborative control system for industrial robots. Detailed Implementation

[0020] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0021] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0022] On modern intelligent manufacturing production lines, multiple industrial robots collaborate to complete complex tasks such as welding, handling, and assembly to ensure smooth and efficient production processes. However, in practical applications, the actual operating time of a single industrial robot can fluctuate unpredictably due to physical environmental factors. These fluctuations accumulate, leading to a time discrepancy between the actual state of the industrial robot and the preset process model of the central system. For example, on an automated automotive chassis production line, multiple industrial robots collaborate to complete the assembly process. The central control system generates detailed motion command sequences and conflict-free motion paths for each industrial robot based on a preset process model.

[0023] However, when the welding robot D is performing its task, the actual welding time is not constant. Factors such as electrode consumption, minor oil or oxide layers on the workpiece surface, and voltage fluctuations can all extend the welding time at a single point. These minor delays accumulate during continuous operation, causing the actual completion time of the industrial robot D to be slower than planned. The central control system plans the entire production cycle based on an idealized welding time. When the actual operation of the industrial robot D is delayed, the subsequent industrial robot E will be idle and waiting because the industrial robot D has not left the site, disrupting the entire production line cycle and reducing efficiency. In this context of minor deviations in the production cycle, when the production line needs to perform global replanning based on changing circumstances to respond to high-priority temporary tasks, the central control system generates new motion commands and paths for the industrial robots based on its internally outdated state model.

[0024] For example, when the system instructs industrial robot A to grasp a special type of suspension bracket and plans to quickly pass through the edge of industrial robot D's work area, in the system model, industrial robot D should have already completed welding and returned to a safe position. However, in reality, due to accumulated delays, industrial robot D is still performing the finishing work on the last weld point, and its welding torch and robotic arm remain within the work area. This asynchrony in information causes industrial robot A's robotic arm to collide with industrial robot D's welding torch when executing new instructions, resulting in equipment damage and production interruption. Existing technologies urgently need improvement to address these issues.

[0025] In this regard, such as Figure 1 As shown, this application proposes a multi-task cooperative control method for industrial robots, including: S101. Obtain the theoretical position information of each industrial robot among multiple industrial robots on the production line after the current moment; the theoretical position information is the position information of the geometric center of the industrial robot.

[0026] S102. For each industrial robot, determine the redundant safety space of the industrial robot based on the theoretical position information of the industrial robot; the industrial robot is located within the redundant safety space during operation.

[0027] S103. In response to the task instruction information for the target industrial robot among multiple industrial robots, determine the task control information of the target industrial robot based on the task instruction information and the redundancy safety space of each industrial robot among the multiple industrial robots.

[0028] This application dynamically acquires the theoretical position information of industrial robots and determines their redundant safety space based on this. Thus, when receiving task instructions, it can comprehensively consider the actual safety boundaries of each industrial robot and generate more accurate and safer task control information, effectively avoiding potential collisions between industrial robots and improving the collaborative efficiency and safety of multi-task operations.

[0029] To better understand the technical solutions proposed in this application, it is necessary to explain some key terms and implementation environments involved. The "industrial robot" referred to in this application refers to machine equipment that performs automated tasks in an industrial production environment, typically consisting of a robotic arm, end effector, controller, etc. On a production line, multiple industrial robots work collaboratively to complete production tasks.

[0030] "Theoretical position information" refers to the ideal position that an industrial robot should be in at a specific moment according to a preset motion planning or task scheduling model. In this application, theoretical position information is defined as the position information of the geometric center of the industrial robot, which helps to simplify calculations and provide a unified reference point.

[0031] "Redundant safety space" refers to a dynamic safety zone defined for an industrial robot based on its theoretical position, taking into account potential motion errors, robotic arm size, end effector range, and other uncertainties. During operation, the industrial robot is required to remain within its redundant safety space at all times to ensure that it avoids collisions with other industrial robots or obstacles, even in the event of minor deviations.

[0032] "Task instruction information" refers to a set of instructions issued to a specific industrial robot to perform a specific production task, such as moving to a certain position, grabbing a certain workpiece, or performing a certain operation.

[0033] "Task control information" refers to the specific motion trajectory, speed, acceleration, and other control parameters generated for the industrial robot based on the task instruction information and the redundant safety space of the industrial robot. It aims to ensure that the industrial robot can not only complete the instruction requirements when performing tasks, but also avoid collisions with the surrounding environment and other industrial robots.

[0034] The implementation environment of this application is typically a smart manufacturing production line, in which multiple industrial robots are deployed and uniformly scheduled and managed through a central control system. This system can acquire the real-time status information of the industrial robots and generate and issue task instructions based on production needs.

[0035] The core of the industrial robot multi-task collaborative control method proposed in this application lies in the accurate determination and application of the redundant safety space of the industrial robot, and the collaborative task control based on this.

[0036] Firstly, the step of "obtaining the theoretical position information of each industrial robot on the production line after the current moment" can be achieved in several ways. For example, a pre-set motion planning or task scheduling system can be used to calculate the theoretical trajectory and position of each industrial robot over a future period (i.e., after the current moment) based on the production plan and process flow. This theoretical position information is typically stored in time series format, with each time point corresponding to the geometric center coordinates of an industrial robot. Another approach is to simulate the motion of all industrial robots on the production line using simulation software and extract the theoretical position data of each robot at future moments from the simulation results. This theoretical position information forms the basis for subsequently determining the redundancy safety space.

[0037] Secondly, the key innovation of this application lies in the step of "determining the redundant safety space of each industrial robot based on its theoretical position information." Determining the redundant safety space requires comprehensive consideration of factors such as the robot's geometry, motion accuracy, and potential error accumulation. One approach is to pre-define a fixed safety envelope for each industrial robot, such as a sphere or cuboid, whose center coincides with the robot's theoretical position, and to determine the size of the envelope based on the robot's maximum dimensions and the pre-determined safety margin.

[0038] However, this fixed envelope approach may be too conservative, limiting the range of motion of the industrial robot. Another approach is to dynamically calculate an envelope region that changes with the robot's posture, based on the robot's theoretical position information, combined with the kinematic model of its robotic arm and the dimensions of the end effector. For example, based on the robot's theoretical posture, a series of small safety zones can be generated around its various joints and links, and the union of these zones can be used as its redundant safety space.

[0039] Finally, the core of collaborative control lies in the step of "responding to task instructions from multiple industrial robots to a target industrial robot, and determining the target industrial robot's task control information based on the task instructions and the redundant safety space of each of the multiple industrial robots." When the system receives a task instruction for a target industrial robot, such as requiring it to move to a new location or perform an operation, the system first generates initial task control information based on the task instruction information, including the target industrial robot's initial motion trajectory and speed planning. Subsequently, the system utilizes the redundant safety space information of all industrial robots to perform collision detection on this initial task control information.

[0040] For example, geometric collision detection can be performed on the initial trajectory of the target industrial robot and the redundant safety space of other industrial robots on the production line. If a potential collision risk is detected, i.e., the trajectory of the target industrial robot will overlap with the redundant safety space of another industrial robot at some point, then the system needs to adjust the initial task control information of the target industrial robot. This adjustment may include modifying the target industrial robot's movement path, reducing its operating speed, or introducing a short waiting time to ensure that the target industrial robot remains outside its own and other industrial robots' redundant safety space while performing the task, thereby avoiding collisions.

[0041] The industrial robot multi-task collaborative control method proposed in this application works by sensing and predicting the state of the industrial robot in real time and dynamically adjusting its safety boundary, thereby achieving efficient and safe collaboration in a multi-task environment.

[0042] Specifically, this method first obtains the theoretical position information of all industrial robots on the production line after the current moment. This theoretical position information is calculated based on a preset production plan and motion model, representing the expected position of the industrial robots under ideal conditions. However, due to various uncertainties in actual production, the actual position of the industrial robots often deviates from the theoretical position. To address this deviation, this application further determines a dynamic redundant safety space for each industrial robot based on its theoretical position information. This redundant safety space not only considers the geometric dimensions of the industrial robot itself but also incorporates its potential motion errors and uncertainties, ensuring that even if the industrial robot experiences minor deviations during operation, it can still be encompassed by this safety space.

[0043] When the production line needs to issue new task instructions to a target industrial robot, such as for emergency order insertion or path adjustment, the system responds to these task instruction information. At this time, the system does not simply generate control information based on the task instructions, but comprehensively considers the task instruction requirements of the target industrial robot as well as the redundant safety space of all industrial robots on the production line. By performing real-time or predictive collision detection between the target industrial robot's expected motion trajectory and the redundant safety space of all other industrial robots, the system can identify potential collision risks. Once a collision risk is detected, the system intelligently adjusts the task control information of the target industrial robot according to the degree and type of risk. This adjustment may include modifying the target industrial robot's motion path to avoid the redundant safety space of other industrial robots, or adjusting its operating speed to stagger its time window with other industrial robots. In this way, this application ensures that the target industrial robot can safely and efficiently collaborate with other industrial robots when performing new tasks, avoiding collision accidents caused by information asynchrony or error accumulation.

[0044] The core innovation of this application lies in the introduction of the concept of "redundant safety space" and its application to the collaborative control of multi-task operations of industrial robots. Unlike the fixed safety distance or ideal-state-based path planning commonly used in existing technologies, the redundant safety space of this application is dynamic and adaptive, which can more accurately reflect the uncertainties of industrial robots in actual operation.

[0045] For example, in traditional industrial robot control methods, a fixed safety zone is typically pre-defined for each industrial robot, or only the robot's geometric outline is considered during path planning. When minor deviations occur on the production line or urgent task replanning is required, these static or idealized safety strategies often fail to cope effectively. As in the background art, if industrial robot D remains within its working area due to accumulated delays, and industrial robot A rapidly traverses it along a pre-defined path, a collision may occur in reality, even if no collision is observed in the ideal model. This is because traditional methods fail to fully consider the deviation between the actual and theoretical positions of the industrial robots, and the cumulative effect of this deviation in a multi-task collaborative environment.

[0046] This application effectively solves the aforementioned problems by acquiring the theoretical position information of industrial robots and dynamically determining their redundant safety space based on this information. The redundant safety space not only includes the geometric center of the industrial robot but also considers its potential motion errors and uncertainties, forming a more realistic and safer dynamic boundary. When the system responds to task commands, it utilizes the redundant safety spaces of all industrial robots for collision detection and adjusts the task control information of the target industrial robot accordingly. This method can identify and avoid potential collision risks in advance, ensuring the safety of collaborative operations even when there are deviations between the actual and theoretical states of the industrial robots. Therefore, this application significantly improves the collaborative efficiency and safety of multi-task operations of industrial robots, reduces the risk of equipment damage and production interruptions, and provides a more reliable solution for flexible production in intelligent manufacturing lines.

[0047] like Figure 2 As shown, this application further proposes a step for determining the redundant safety space of an industrial robot based on its theoretical position information, including: S201. Obtain the historical theoretical position information and historical actual position information of the industrial robot at each historical moment in multiple historical moments; S202. Determine the spatial redundancy distance of the industrial robot based on the historical theoretical position information and historical actual position information of each historical moment in multiple historical moments. S203. Determine the redundant safety space of the industrial robot based on the spatial redundancy distance and the theoretical position information of the industrial robot.

[0048] Specifically, acquiring the historical theoretical position information and historical actual position information of an industrial robot at each historical moment across multiple historical periods refers to periodically recording data on the robot's preset theoretical trajectory points and actual arrival points over a past period, using the robot's control system or external sensors. The historical theoretical position information can be understood as the geometric center position that the industrial robot should reach according to its programming instructions, while the historical actual position information is the true position of the robot's geometric center obtained in real time through high-precision positioning sensors (such as laser trackers, vision systems, or encoder feedback). This historical data is used to quantify the inherent uncertainties in the operation of industrial robots.

[0049] Specifically, determining the spatial redundancy distance of the industrial robot based on its historical theoretical and actual position information at each historical moment across multiple historical data points can be understood as calculating the degree of deviation between the robot's actual position and its theoretical position through statistical analysis of this historical data. This spatial redundancy distance aims to characterize the maximum possible deviation between the industrial robot's actual trajectory and its theoretical trajectory, with the purpose of providing a quantified safety margin for the subsequent construction of redundant safety spaces.

[0050] In practical applications, the redundant safety space of an industrial robot is determined based on its spatial redundancy distance and theoretical position information. Specifically, this means constructing a geometric region around the robot that encompasses all possible actual positions, using its theoretical position information as a benchmark and the determined spatial redundancy distance. This redundant safety space is a dynamically adjusted region, its boundaries determined by both the theoretical position and the spatial redundancy distance, ensuring that even with deviations during operation, the robot's body remains completely contained within this safety space.

[0051] This application's solution, by introducing historical theoretical and historical actual position information, enables quantitative analysis of the uncertainties in the actual operation of industrial robots. By comparing the historical theoretical and actual position information of the industrial robot at multiple historical moments, the deviation between the actual trajectory and the theoretical trajectory can be accurately calculated, thereby determining the spatial redundancy distance of the industrial robot. This spatial redundancy distance reflects the inherent errors and uncertainties in the operation of the industrial robot. Subsequently, by combining this spatial redundancy distance with the theoretical position information of the industrial robot, a more accurate and adaptive redundant safety space can be constructed. This method avoids the inaccuracy of the safety space that may result from relying solely on theoretical position information, allowing the determined redundant safety space to more realistically reflect the area occupied by the industrial robot during actual operation, thus effectively solving the problem of unreasonable safety space settings in traditional methods.

[0052] Specifically, in the aforementioned multi-task collaborative control method for industrial robots, the step of determining the spatial redundancy distance of the industrial robot based on the historical theoretical position information and historical actual position information of each historical moment in multiple historical moments can specifically include: Based on the historical theoretical position information and historical actual position information of each historical moment in multiple historical moments, the root mean square error between the historical theoretical position information and the historical actual position information is determined; the safety factor of the industrial robot is obtained; and the product of the root mean square error and the safety factor of the industrial robot is used as the spatial redundancy distance of the industrial robot.

[0053] Historical theoretical position information refers to the ideal position that an industrial robot should reach at a certain point in the past, based on its preset motion trajectory or control commands. Historical actual position information refers to the actual position detected by the industrial robot at that historical moment through sensors or other positioning systems. Root mean square error (RMSE) is a statistical measure of the deviation between the theoretical and actual values. It is typically calculated by summing the squared Euclidean distances between the theoretical and actual position information at each historical moment, taking the average, and then taking the square root. This RMSE reflects the average degree to which the industrial robot deviates from its theoretical trajectory during actual operation and can be used as an indicator of its positioning accuracy.

[0054] The safety factor of an industrial robot is a multiplier factor used to adjust the size of the redundant safety space, and its value is typically greater than 1. This safety factor can be set according to factors such as the actual application scenario, production line safety requirements, and the operating status of the industrial robot. For example, in scenarios with high safety requirements, a larger safety factor can be used to provide a greater safety margin; conversely, in scenarios with higher efficiency requirements and controllable risks, a smaller safety factor can be used. Therefore, by multiplying the root mean square error (RMSE) by the safety factor of the industrial robot, the spatial redundancy distance of the industrial robot can be obtained. This spatial redundancy distance comprehensively considers the positioning accuracy error of the industrial robot and the required additional safety margin.

[0055] The proposed solution determines the spatial redundancy distance of an industrial robot by introducing root mean square error (RMSE) and a safety factor. Its working principle is as follows: First, by calculating the RMSE between the theoretical and actual historical position information of the industrial robot at multiple historical moments, the positioning uncertainty or error range of the industrial robot during actual operation can be objectively quantified. This error is inherent to the industrial robot's motion control system and changes with time, wear, and other factors.

[0056] Secondly, a safety factor is introduced to amplify or adjust the quantified error, providing additional safety margin. This safety factor can be dynamically adjusted based on the external environment (such as production line safety level) and the industrial robot's own state (such as maintenance status and operating time), ensuring that the determined spatial redundancy distance not only reflects the industrial robot's positioning accuracy but also takes into account the safety requirements of both the external environment and internal conditions. Finally, multiplying the root mean square error by the safety factor allows the spatial redundancy distance to more comprehensively and accurately characterize the actual space range that the industrial robot may occupy during operation, thus providing a reliable basis for subsequent collaborative control.

[0057] This application further proposes a method for obtaining the safety factor of an industrial robot, including: Obtain the safety requirement index of the production line and the first correspondence relationship; the first correspondence relationship includes a one-to-one correspondence between multiple safety requirement index ranges and multiple first safety coefficients; the first safety coefficient corresponding to the safety requirement index range in which the production line's safety requirement index falls in the first correspondence relationship is taken as the production line safety coefficient; obtain the running time of the industrial robot after the last maintenance and the second correspondence relationship; the second correspondence relationship includes a one-to-one correspondence between multiple running time ranges and multiple second safety coefficients; the second safety coefficient corresponding to the running time range in which the industrial robot's running time falls in the second correspondence relationship is taken as the running time safety coefficient; the weighted sum of the production line safety coefficient and the running time safety coefficient is taken as the industrial robot's safety coefficient.

[0058] Specifically, the safety requirement index of a production line refers to a quantitative indicator reflecting the overall safety level and risk tolerance of the production line. For example, it can be assessed and classified based on factors such as the production environment, equipment density, and frequency of personnel activity. Its purpose is to provide differentiated safety guarantees for production lines with different safety requirements. The first correspondence can be understood as a pre-established lookup table or function relationship used to map different safety requirement index ranges to corresponding safety coefficients. For example, the higher the safety requirement index, the larger the corresponding first safety coefficient may be, providing a higher safety margin. The running time of an industrial robot since its last maintenance refers to the cumulative running time of the industrial robot since its last comprehensive inspection, maintenance, or repair. Its purpose is to assess the potential risks such as wear and tear and decreased precision that may occur due to long-term operation.

[0059] The second correspondence can be understood as another lookup table or function relationship, used to map different runtime ranges to corresponding safety factors. For example, the longer the runtime, the larger the corresponding second safety factor may be, to compensate for uncertainties that may arise due to equipment aging. In practical applications, the production line safety factor is obtained from the first correspondence based on the production line's safety requirement index, reflecting the production line environment's requirements for the safety factor. The runtime safety factor is obtained from the second correspondence based on the industrial robot's runtime since its last maintenance, reflecting the impact of the industrial robot's own condition on the safety factor. Ultimately, the industrial robot's safety factor is calculated by weighting and summing the production line safety factor and the runtime safety factor. The weighting coefficient can be set according to actual needs and experience to balance the impact of the production line environment and the robot's own condition on the overall safety factor.

[0060] This application's solution dynamically and precisely determines the safety factor of an industrial robot by comprehensively considering two key factors: the safety requirement index of the production line and the runtime of the industrial robot since its last maintenance. The safety requirement index of the production line reflects the safety requirements of the external environment, while the runtime of the industrial robot since its last maintenance reflects the impact of the robot's internal condition (such as wear and tear, decreased precision, etc.) on safety. By mapping these two factors to their corresponding safety factors and then performing a weighted sum, the final safety factor of the industrial robot can more comprehensively and accurately reflect the actual safety risks currently faced by the industrial robot. It is precisely because of this multi-dimensional and dynamic safety factor determination mechanism that the determined spatial redundancy distance can better adapt to different operating scenarios and robot states, avoiding the inaccuracies that may be caused by a single or fixed safety factor.

[0061] This application further proposes that the position information of the industrial robot includes the theoretical position information of the industrial robot at each time after the current time. Based on the spatial redundancy distance of the industrial robot and the theoretical position information, a redundant safety space for the industrial robot is determined, including: Obtain the outline of the industrial robot; for each time point after the current time, use the theoretical position information of the industrial robot as the geometric center of the initial redundant safety space, and use the spatial redundancy distance corresponding to each time point as the distance from the boundary of the initial redundant safety space of the industrial robot to the corresponding position of the outline of the industrial robot, thus obtaining the initial redundant safety space of the industrial robot; the outline of the initial redundant safety space of the industrial robot is similar to the outline of the industrial robot; obtain the planned running speed of the industrial robot at each time point after the current time; for each time point after the current time, adjust the initial redundant safety space of the industrial robot according to the planned running speed of the industrial robot at each time point, thus obtaining the redundant safety space of the industrial robot.

[0062] Specifically, obtaining the contour of an industrial robot refers to acquiring its precise geometric shape information through methods such as pre-measurement, 3D scanning, or extraction from a design model. This contour information can be 3D model data of the industrial robot, such as point clouds, mesh models, or parametric models, used to accurately describe the physical boundaries of the industrial robot.

[0063] In this method, the theoretical position information of the industrial robot is used as the geometric center of the initial redundant safety space, and the spatial redundancy distance at each moment is used as the distance from the boundary of the initial redundant safety space to the corresponding position of the robot's outline. This means that the initial redundant safety space is not a simple sphere or cube, but rather a safety area that is similar to, but slightly enlarged, the actual shape of the industrial robot, based on its theoretical position and combined with its actual outline and spatial redundancy distance. For example, if the industrial robot has an L-shaped arm, its initial redundant safety space will also be L-shaped, and the distance between its boundary and the robot's outline is determined by the spatial redundancy distance.

[0064] In practical applications, obtaining the planned operating speed of an industrial robot at each subsequent moment serves as a crucial input for dynamic adjustments to the redundancy safety space. The planned operating speed can be obtained from a task planning system or motion controller, reflecting the robot's expected motion state over a future period.

[0065] Furthermore, for each subsequent moment, the initial redundant safety space of the industrial robot is adjusted according to its planned operating speed at each moment, resulting in the redundant safety space of the industrial robot. This adjustment process aims to enable the redundant safety space to dynamically adapt to the robot's motion state. For example, when the industrial robot is running at high speed, its inertia is large, requiring a larger safety margin; when it is running at low speed, the safety space can be appropriately reduced to improve space utilization.

[0066] The solution proposed in this application incorporates the contour information of the industrial robot, enabling the shape of the initial redundant safety space to more accurately match the actual physical dimensions and geometric features of the industrial robot. This avoids the problem of mismatch between the safety space and the actual shape of the robot that may exist in traditional methods. Because the contour of the initial redundant safety space is similar to the contour of the industrial robot, the determined safety space can more realistically reflect the area occupied by the industrial robot, thereby improving the accuracy of the safety space.

[0067] Based on this, by acquiring the planned operating speed of the industrial robot at future moments, the initial redundant safety space is dynamically adjusted accordingly. This allows the redundant safety space to adaptively change based on the actual motion state of the industrial robot. For example, during high-speed movement, the safety space can be appropriately enlarged or lengthened along the direction of movement to reserve sufficient braking distance and reaction time; during low-speed or stationary movement, the safety space can be appropriately reduced to improve space utilization. This dynamic adjustment mechanism effectively solves the limitations of determining the safety space solely based on static theoretical position and spatial redundancy distance, ensuring that the safety space meets both safety requirements and operational efficiency.

[0068] Through the above technical solutions, the determined redundant safety space for industrial robots can more accurately reflect the actual physical occupancy and dynamic motion characteristics of the robots. Specifically, by considering the outline of the industrial robot, the problem of discrepancies between the safety space and reality caused by simplified models is avoided, thus improving the accuracy of the safety space. Simultaneously, by dynamically adjusting the safety space according to the planned operating speed, the safety space can adaptively adapt to the motion state of the industrial robot. This maximizes the utilization of the workspace while ensuring safety, effectively reducing collision risks and improving the flexibility and efficiency of multi-robot collaborative operations.

[0069] This application further proposes a more refined adjustment method, which involves introducing a stretching coefficient to stretch the initial redundant safety space along the direction of movement of the industrial robot, so as to more accurately reflect the safety requirements of the industrial robot in dynamic operation.

[0070] The initial redundancy safety space of the industrial robot is adjusted according to the planned operating speed of the industrial robot at each moment to obtain the redundancy safety space of the industrial robot. Specifically, this includes: obtaining a third correspondence for each moment after the current moment; the third correspondence includes a one-to-one correspondence between multiple operating speed ranges and multiple stretching coefficients; taking the stretching coefficient corresponding to the operating speed range of the planned operating speed of the industrial robot at each moment in the third correspondence as the target stretching coefficient for each moment; stretching the initial redundancy safety space of the industrial robot along the direction of movement of the industrial robot according to the target stretching coefficient for each moment to obtain the redundancy safety space of the industrial robot.

[0071] The third correspondence can be understood as a pre-established set of rules guiding the dynamic adjustment of the redundant safety space. This correspondence divides the operating speed of the industrial robot into multiple discrete or continuous speed ranges, and presets a corresponding stretching factor for each speed range. For example, when the operating speed is low, the stretching factor may be close to 1, indicating that the safety space only needs minor adjustments; while when the operating speed is high, the stretching factor will increase significantly to ensure sufficient buffer and reaction space under high-speed movement. This third correspondence can be established and optimized through experimental data, simulation, or expert experience, with the aim of ensuring that the redundant safety space can dynamically adapt to the actual operating state of the industrial robot.

[0072] Specifically, the stretching factor is a dimensionless multiplier factor used to expand the initial redundancy safety space in a specific direction. Once the planned operating speed of the industrial robot at each moment is determined, the system queries the third correspondence to find the operating speed range within which the planned operating speed falls, and obtains the stretching factor corresponding to that range, using it as the target stretching factor for that moment.

[0073] In practical applications, stretching the initial redundant safety space along the direction of industrial robot movement refers to expanding the size of the initial redundant safety space according to a target stretching factor along the expected trajectory of the industrial robot. For example, if the initial redundant safety space is a sphere or cube, after the stretching operation, it may become an ellipsoid or cuboid, with its major axis aligned with the direction of industrial robot movement, and its length determined by the target stretching factor. The purpose is that when the industrial robot moves at high speed, its inertia, braking distance, and potential path deviations will cause it to occupy a larger actual space in the direction of movement; the stretching operation can more accurately cover this dynamic safety area.

[0074] This application's solution addresses the problem of insufficient dynamic adaptability of redundant safety space at different operating speeds by introducing a third correspondence and an elongation coefficient. When the planned operating speed of the industrial robot changes, the system can dynamically acquire a target elongation coefficient matching the current speed based on a preset third correspondence. Because this target elongation coefficient reflects the dynamic characteristics of the industrial robot at different speeds, such as inertial effects and braking distance, the initial redundant safety space can be specifically elongated along the robot's direction of motion. This elongation operation along the direction of motion effectively incorporates the additional space occupied by the industrial robot due to inertia or braking requirements during high-speed movement into the redundant safety space, thereby ensuring that the industrial robot remains within its dynamic redundant safety space throughout the entire operation, avoiding the problems of insufficient or overly conservative safety space caused by speed changes.

[0075] Through the above technical solution, this application enables dynamic adaptive adjustment of the redundant safety space, allowing it to more accurately reflect the actual safety requirements of industrial robots at different operating speeds. Compared to solutions that only make general adjustments based on planned operating speeds, this application introduces a correspondence between the operating speed range and the stretching coefficient, and stretches it along the direction of motion. This allows the redundant safety space to effectively cover the additional space requirements caused by inertia and increased braking distance during high-speed movement while maintaining its compactness. Therefore, this not only significantly improves the safety of collaborative operation of industrial robots and reduces collision risks, but also avoids the decline in operational efficiency caused by overly conservative safety space settings. Thus, it maximizes the overall operational efficiency of the production line while ensuring safety.

[0076] This application further proposes the following steps for determining the task control information of the target industrial robot: In response to task command information from multiple industrial robots for a target industrial robot, the initial task control information of the target industrial robot is determined based on the task command information. The initial task control information includes the initial position information and initial running speed of the target industrial robot at each moment during task execution. The position information of the target industrial robot at each moment during task execution and the redundant safety space of each of the multiple industrial robots are input into a preset geometric collision detection model to obtain the minimum distance between the target industrial robot and the redundant safety space of each industrial robot at each moment during task execution. The moment when the corresponding minimum distance is less than 0 is taken as the target moment. The initial task control information of the target industrial robot is adjusted according to the minimum distance corresponding to the target moment to obtain and execute the adjusted task control information.

[0077] Specifically, initial task control information refers to the preliminary planned motion trajectory and velocity curve of the target industrial robot based on its task instructions, without considering the dynamic influence of other industrial robots. This information includes the position and speed that the target industrial robot should reach at various points in time during the future execution of the task. Its purpose is to provide a basic motion plan for subsequent collision detection and path adjustment.

[0078] The pre-defined geometric collision detection model can be understood as an algorithm or computational module that receives the position information of the target industrial robot at each moment during task execution, as well as the redundant safety space of other industrial robots, as input, and calculates the geometric distance between the target industrial robot and the redundant safety space of any other industrial robot on its planned path. This model can assess potential collision risks in real-time or near real-time, aiming to identify whether the target industrial robot will intrude into the redundant safety space of other industrial robots, or whether other industrial robots will intrude into the redundant safety space of the target industrial robot.

[0079] In practical applications, the minimum distance refers to the shortest distance between the target industrial robot and the redundant safety space of other industrial robots around it at a certain moment, calculated by a preset geometric collision detection model. When this minimum distance is less than 0, it indicates that the target industrial robot has already intruded into or is about to intrude into the redundant safety space of other industrial robots, i.e., there is a risk of collision.

[0080] The target moment refers to the specific time point within the path planned by the initial task control information of the target industrial robot where the minimum distance is detected to be less than 0. These moments are critical time points where task control information needs to be adjusted, with the aim of accurately locating the time point when collision risks occur so that targeted adjustments can be made.

[0081] Adjusting the initial task control information refers to modifying the initial position or initial operating speed of the target industrial robot based on the minimum distance detected at the target time, in order to eliminate or mitigate the risk of collision. The adjusted task control information will be executed to ensure that the target industrial robot can complete the task safely and without collision.

[0082] This application's solution effectively addresses the dynamic collision risks inherent in traditional methods by introducing an explicit collision detection and task control information adjustment mechanism. Specifically, firstly, initial task control information is generated for the target industrial robot based on task instruction information, representing its ideal motion trajectory. Then, using a pre-defined geometric collision detection model, the target industrial robot's position information is compared with the redundant safety spaces of other industrial robots on the production line, thereby calculating the minimum distance between the target industrial robot and each redundant safety space in real time. When the minimum distance is detected to be less than 0, a potential collision risk is identified, and this moment is marked as the target moment.

[0083] Because the system can accurately identify the timing and extent of potential collisions, it can make targeted adjustments to the initial task control information of the target industrial robot based on the minimum distance corresponding to the target moment. These adjustments can change the target industrial robot's path, speed, or timing to ensure it remains within a safe range while performing its task, avoiding collisions with other industrial robots.

[0084] Through the above technical solution, this application enables more refined and safer collaborative control of multi-task operations of industrial robots. Compared to basic solutions that rely solely on redundant safety spaces for rough planning, this application significantly improves the safety of multi-robot collaborative operations by introducing dynamic geometric collision detection and real-time task control information adjustment. This solution can proactively identify and avoid potential collision risks, preventing collisions caused by robot path intersections or unexpected situations, thereby effectively protecting equipment and personnel safety. Furthermore, through intelligent adjustment of task control information, the robot's motion trajectory can be optimized, improving operational efficiency, reducing unnecessary downtime, and ultimately enhancing the overall production line's productivity.

[0085] This application further proposes that when the absolute value of the minimum distance at the target time is less than a first distance threshold, the initial position information of the target industrial robot at the target time is translated along the target direction by the absolute value of the minimum distance, so as to obtain and execute the adjusted task control information.

[0086] Specifically, when adjusting the initial task control information of the target industrial robot, the first step is to determine whether the absolute value of the minimum distance at the target moment is less than a preset first distance threshold. This first distance threshold can be understood as a boundary value used to distinguish the severity of a collision. It can be set based on factors such as the size of the industrial robot, its operating speed, and the safety level of the production line, with the aim of identifying minor collision risks.

[0087] When the judgment result shows that the absolute value of the minimum distance at the target time is less than the first distance threshold, it indicates that the collision risk is relatively small, or that the overlap between the two industrial robots is minor. At this point, the initial position information of the target industrial robot at the target time is translated along the target direction by the absolute value of the minimum distance. Here, the target direction refers to the direction in which the pre-collision industrial robot points towards the target industrial robot. The pre-collision industrial robot is defined as the industrial robot whose minimum distance between its redundant safety space and the target industrial robot at the target time is less than or equal to 0. The adjusted task control information is then obtained and executed.

[0088] This application's solution introduces a first distance threshold to meticulously differentiate collision risks. When the absolute value of the detected minimum distance is small, indicating a minor collision, adjustments are made by shifting the absolute value of the minimum distance along the target direction. This adjustment method precisely eliminates minor overlaps, avoiding unnecessary significant path modifications or sudden speed drops, thus maximizing the maintenance of the industrial robot's original task trajectory and operational efficiency while ensuring safety. It is precisely because of this targeted adjustment strategy that the industrial robot can take the most appropriate and efficient countermeasures when facing collision risks of varying degrees.

[0089] Through the above technical solution, this application can provide more refined task control information adjustment strategies based on the severity of collision risks. Especially for minor collisions or overlaps, precise positional translation along the target direction can effectively eliminate collision risks while avoiding reduced operational efficiency and resource waste caused by over-adjustment. This differentiated approach makes the collaborative operation of industrial robots more flexible and efficient, significantly improving the overall operational efficiency and safety of the production line.

[0090] This application further proposes adjusting the initial task control information of the target industrial robot when the absolute value of the minimum distance at the target time is greater than or equal to a first distance threshold, to obtain and execute the adjusted task control information. This adjustment includes: The planned operating speed of the pre-collision industrial robot within a preset time period before the target time is reduced by a preset speed step; the operating speed of the target industrial robot within a preset time period before the target time is reduced by a preset speed step, thus obtaining the initially adjusted task control information.

[0091] Specifically, a pre-collision industrial robot refers to an industrial robot whose minimum distance between the redundant safety space and the target industrial robot at the target time is less than or equal to 0, meaning a robot with a potential collision risk with the target industrial robot. The preset duration refers to a period of time before the target time, used to adjust the robot's operating speed in advance to provide sufficient reaction time. The preset speed step size refers to the amount of speed reduction during each adjustment, the magnitude of which can be set according to actual needs, robot performance, and safety requirements. By reducing the planned operating speeds of the pre-collision industrial robot and the target industrial robot within the preset duration before the target time, the relative approach speed between them can be effectively slowed down, thus creating more time and space to avoid a collision.

[0092] The proposed solution, when a significant potential collision risk is detected—specifically, when the absolute value of the minimum distance at the target time is greater than or equal to a first distance threshold—moves beyond mere positional adjustments to employ a more proactive speed adjustment strategy. Specifically, by simultaneously reducing the operating speeds of both the pre-collision industrial robot and the target industrial robot for a preset time period before the target time, the time it takes for both to reach the potential collision point is effectively extended, thereby increasing the system's margin for further judgment, planning, or adjustment. This speed reduction smoothly alters the robot's motion state, avoiding shocks or instability caused by sudden position adjustments, allowing the robot to avoid collisions in a more controlled manner. Furthermore, the advance speed reduction provides a valuable time window for potentially more refined path planning or task scheduling later on.

[0093] Through the aforementioned technical solutions, this application enables more refined and effective countermeasures against potential collision risks of varying degrees. Particularly for more severe collision risks, by preemptively reducing the operating speed of the relevant industrial robots, collisions can be effectively avoided, and the robot's trajectory can be made smoother, reducing system impact and energy loss caused by emergency braking or sharp trajectory changes. This strategy significantly improves the safety and robustness of the industrial robot's multi-task collaborative control system, while optimizing the overall operating efficiency and stability of the production line, preventing downtime or equipment damage due to collisions, thereby reducing operating costs.

[0094] This application also discloses a multi-task collaborative control system for industrial robots, comprising: an acquisition device and a processing device; the acquisition device is used to acquire the theoretical position information of each of the multiple industrial robots on the production line after the current moment; the theoretical position information is the position information of the geometric center of the industrial robot; the processing device is used to determine the redundant safety space of each industrial robot based on the theoretical position information of the industrial robot; the industrial robot is located within the redundant safety space during operation; the processing device is used to determine the task control information of the target industrial robot in response to the task instruction information of the multiple industrial robots for the target industrial robot, based on the task instruction information and the redundant safety space of each of the multiple industrial robots.

[0095] It is important to emphasize that the acquisition device, as a component of the system, can be implemented in ways that include, but are not limited to: a data interface module configured to receive pre-calculated theoretical position data streams of the industrial robot from the motion planning module or simulation module of the central control system. For example, this data interface module can be an Ethernet interface or a fiber optic interface, interacting with the host computer or simulation server via standard communication protocols (such as OPCUA, EtherCAT, etc.).

[0096] It is important to emphasize that the processing device, as a component of the system, can be implemented in ways that include, but are not limited to: a high-performance computing unit, such as an embedded controller or industrial PC, running a specific algorithm module. This algorithm module is configured to receive theoretical position information from the acquisition device and, in conjunction with the industrial robot's geometric model, kinematic parameters, and a preset safety margin, calculate and generate a dynamic redundant safety space. For example, this algorithm can be based on an envelope algorithm (such as a minimum bounding box, minimum bounding sphere, or OBB) or a point cloud dilation algorithm to construct a dynamically changing safety region around the industrial robot, capable of encompassing its potential motion errors, based on the robot's theoretical posture and dimensions.

[0097] The above are merely embodiments of this application and are not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for multi-task collaborative control of an industrial robot, characterized in that, include: Obtain the theoretical position information of each industrial robot on the production line after the current moment; the theoretical position information is the position information of the geometric center of the industrial robot. For each industrial robot, the redundant safety space of the industrial robot is determined based on the theoretical position information of the industrial robot; the industrial robot is located within the redundant safety space during operation; In response to task instruction information for the target industrial robot from multiple industrial robots, the task control information for the target industrial robot is determined based on the task instruction information and the redundancy safety space of each industrial robot.

2. The multi-task collaborative control method for industrial robots according to claim 1, characterized in that, The redundant safety space of the industrial robot is determined based on its theoretical position information, including: Acquire the historical theoretical position information and historical actual position information of the industrial robot at each historical moment in multiple historical moments; The spatial redundancy distance of the industrial robot is determined based on the historical theoretical location information and historical actual location information of each historical moment in multiple historical moments. The redundant safety space of the industrial robot is determined based on the spatial redundancy distance and the theoretical position information of the industrial robot.

3. The multi-task collaborative control method for industrial robots according to claim 2, characterized in that, Based on the historical theoretical location information and historical actual location information of each historical moment in multiple historical moments, the spatial redundancy distance of the industrial robot is determined, including: Based on the theoretical and actual historical location information of each historical moment in multiple historical moments, determine the root mean square error between the theoretical and actual historical location information. Obtain the safety factor of industrial robots; The product of the root mean square error and the safety factor of the industrial robot is used as the spatial redundancy distance of the industrial robot.

4. The multi-task collaborative control method for industrial robots according to claim 3, characterized in that, Obtaining the safety factor of industrial robots includes: Obtain the safety requirement index of the production line and the first correspondence relationship; the first correspondence relationship includes a one-to-one correspondence between multiple safety requirement index ranges and multiple first safety coefficients; The first safety factor corresponding to the safety requirement index range of the production line in the first correspondence relationship is taken as the production line safety factor. Obtain the runtime of the industrial robot after the last maintenance and the corresponding relationship between the second and the second relationship; the second relationship includes a one-to-one correspondence between multiple runtime ranges and multiple second safety factors. The second safety factor corresponding to the range of operating time after the last maintenance of the industrial robot in the second correspondence is used as the operating time safety factor. The weighted sum of the production line safety factor and the runtime safety factor is used as the safety factor for industrial robots.

5. The multi-task collaborative control method for industrial robots according to claim 2, characterized in that, The position information of the industrial robot includes the theoretical position information of the industrial robot at every moment after the current moment. The redundant safety space of the industrial robot is determined based on the spatial redundancy distance and the theoretical position information, including: Obtain the outline of the industrial robot; For each time point after the current time, the theoretical position information of the industrial robot is used as the geometric center of the initial redundant safety space, and the spatial redundancy distance corresponding to each time point is used as the distance from the boundary of the initial redundant safety space of the industrial robot to the corresponding position of the outline of the industrial robot, thus obtaining the initial redundant safety space of the industrial robot; the outline of the initial redundant safety space of the industrial robot is similar to the outline of the industrial robot. Obtain the planned operating speed of the industrial robot at each time step after obtaining the current time step; For each time point after the current time, the initial redundancy safety space of the industrial robot is adjusted according to the planned operating speed of the industrial robot at each time point to obtain the redundancy safety space of the industrial robot.

6. The multi-task collaborative control method for industrial robots according to claim 5, characterized in that, The initial redundancy safety space of the industrial robot is adjusted according to its planned operating speed at various times, resulting in the redundancy safety space of the industrial robot, which includes: For each time point after the current time, obtain the third correspondence; the third correspondence includes a one-to-one correspondence between multiple operating speed ranges and multiple stretching coefficients; The stretching factor corresponding to the planned operating speed range of the industrial robot at each moment in the third correspondence is taken as the target stretching factor at each moment. Along the direction of movement of the industrial robot, the initial redundant safety space corresponding to the industrial robot is stretched according to the target stretching coefficient at each moment to obtain the redundant safety space of the industrial robot.

7. The multi-task collaborative control method for industrial robots according to claim 1, characterized in that, In response to task instruction information for a target industrial robot from multiple industrial robots, and based on the task instruction information and the redundancy safety space of each of the multiple industrial robots, the task control information of the target industrial robot is determined, including: In response to task command information from multiple industrial robots to the target industrial robot, the initial task control information of the target industrial robot is determined based on the task command information; the initial task control information includes the initial position information and initial running speed of the target industrial robot at each moment when performing the task; The position information of the target industrial robot at each moment when performing the task and the redundant safety space of each industrial robot among multiple industrial robots are input into the preset geometric collision detection model to obtain the minimum distance between the target industrial robot and the redundant safety space of each industrial robot at each moment when performing the task. The moment when the minimum distance is less than 0 is taken as the target moment; The initial task control information of the target industrial robot is adjusted based on the minimum distance corresponding to the target time, and the adjusted task control information is obtained and executed.

8. The multi-task collaborative control method for industrial robots according to claim 7, characterized in that, The initial task control information of the target industrial robot is adjusted based on the minimum distance corresponding to the target time, and the adjusted task control information is obtained and executed, including: Determine whether the absolute value of the minimum distance corresponding to the target time is less than the first distance threshold; When the absolute value of the minimum distance at the target time is less than the first distance threshold, the initial position information of the target industrial robot at the target time is translated along the target direction by the absolute value of the minimum distance to obtain and execute the adjusted task control information; the target direction is the direction from which the pre-collision industrial robot points to the target robot, and the pre-collision industrial robot is the industrial robot whose minimum distance between the redundant safety space and the target industrial robot at the target time is less than or equal to 0.

9. The multi-task collaborative control method for industrial robots according to claim 8, characterized in that, When the absolute value of the minimum distance at the target time is greater than or equal to the first distance threshold, the initial task control information of the target industrial robot is adjusted to obtain and execute the adjusted task control information, including: Reduce the planned operating speed of the pre-collision industrial robot by a preset speed step within a preset time period before the target moment; The operating speed of the target industrial robot is reduced by a preset speed step within a preset time period before the target time to obtain the initially adjusted task control information.

10. A multi-task collaborative control system for industrial robots, characterized in that, include: Acquisition device and processing device; Acquisition device, used to acquire the theoretical position information of each of the multiple industrial robots on the production line after the current moment; The theoretical position information is the position information of the geometric center of the industrial robot; The processing device is used to determine the redundant safety space of each industrial robot based on the theoretical position information of the industrial robot; the industrial robot is located within the redundant safety space during operation. The processing unit is used to respond to task instruction information for a target industrial robot from multiple industrial robots, and to determine the task control information of the target industrial robot based on the task instruction information and the redundancy safety space of each industrial robot.

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